# Knock-Prediction System for Kerosene Engines Using In-Cylinder Pressure Signal

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## Abstract

**:**

## 1. Introduction

## 2. Experimental System

## 3. Knock-Prediction Model

#### 3.1. Analysis of Knock

#### 3.2. Establishment of the Prediction Model

^{T}φ(x) + b can be calculated. ω

^{T}φ(x) + b is proportional to d, so ω

^{T}φ(x) + b can be used to indicate the knock margin.

## 4. Design of the Kerosene Engine Knock-Prediction System

#### 4.1. Outline of the Estimation System

#### 4.2. In-Cylinder Pressure Signal Decomposition

#### 4.3. Feature Extraction

## 5. Results and Discussion

## 6. Conclusions

## Author Contributions

## Funding

## Institutional Review Board Statement

## Informed Consent Statement

## Data Availability Statement

## Conflicts of Interest

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Item | Parameter |
---|---|

Two-stroke kerosene engine | Port fuel injection |

Displacement | 275 mL |

Compression ratio | 7.4 |

Bore | 66 mm |

Stroke | 40 mm |

Max power | 16 kw |

Cooling method | Air cooling |

Exhaust port opening | 102 °CA ATDC |

Exhaust port closing | 246 °CA ATDC |

Scavenging port opening | 114 °CA ATDC |

Scavenging port closing | 258 °CA ATDC |

**Table 2.**Center frequency and pressure amplitude of each IMF component of in-cylinder pressure signal.

Intrinsic Mode Function | Pressure (MPa) | Center Frequency (KHz) |
---|---|---|

IMF1 | 3.42 × 10^{−3} | 44.98 |

IMF2 | 1.84 × 10^{−3} | 28.07 |

IMF3 | 5.61 × 10^{−3} | 8.58 |

Principal Components | 1 | 2 | 3 | 4 | 5 |
---|---|---|---|---|---|

Variance Explained | 58% | 19% | 14% | 5% | 2% |

Signal-Processing Method | Feature Extraction | SVM | Logistic Regression |
---|---|---|---|

Raw data | TDSA | 91.29% | 88.93% |

Wavelet decomposition | TDSA | 95.43% | 92.21% |

EMD | TDSA | 97.29% | 95.07% |

TDSA + PCA | 96.71% | 93.64% |

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**MDPI and ACS Style**

Xu, Z.; Cao, G.; Wei, M.; Zhao, Z.; Xing, Z.; Ding, Y.
Knock-Prediction System for Kerosene Engines Using In-Cylinder Pressure Signal. *Energies* **2023**, *16*, 2766.
https://doi.org/10.3390/en16062766

**AMA Style**

Xu Z, Cao G, Wei M, Zhao Z, Xing Z, Ding Y.
Knock-Prediction System for Kerosene Engines Using In-Cylinder Pressure Signal. *Energies*. 2023; 16(6):2766.
https://doi.org/10.3390/en16062766

**Chicago/Turabian Style**

Xu, Zhixin, Guangzhou Cao, Minxiang Wei, Zhuowen Zhao, Zhiyu Xing, and Yuzhang Ding.
2023. "Knock-Prediction System for Kerosene Engines Using In-Cylinder Pressure Signal" *Energies* 16, no. 6: 2766.
https://doi.org/10.3390/en16062766